Stepwise regression is a statistical technique used for model selection. This package streamlines stepwise regression analysis by supporting multiple regression types(linear, Cox, logistic, Poisson, Gamma, and negative binomial), incorporating popular selection strategies(forward, backward, bidirectional, and subset), and offering essential metrics. It enables users to apply multiple selection strategies and metrics in a single function call, visualize variable selection processes, and export results in various formats. StepReg offers a data-splitting option to address potential issues with invalid statistical inference and a randomized forward selection option to avoid overfitting. We validated StepReg's accuracy using public datasets within the SAS software environment. For an interactive web interface, users can install the companion 'StepRegShiny' package.
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Dependency Anatomy Guide
Understanding Dependency Borders
Dependencies are visually distinguished by their border styles to help you understand their relationship to the current package:
Direct Dependencies
Thick solid border: These are dependencies directly specified in the package's DESCRIPTION file (Depends, Imports, Enhances, or LinkingTo).
Recursive Dependencies
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Version Constraint Conflicts
Thick border + Info icon: When both direct and recursive dependencies exist for the same package with different version constraints. This indicates the "true" version constraint for the package, as the recursive dependency requires the more strict version constraint.
Understanding the Info Icon
The yellow info circle appears when there are version constraint conflicts between direct and recursive dependencies for the same package. This helps give a more accurate picture of the version constraints for the dependencies of a given package.